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Data Compliance: Can AI Help Users Navigate New Technologies and Regulations?

Automation is transforming compliance. Can labs keep up with new demands?

Article  
Published: November 13, 2025 
RJ Mackenzie
 speaking with 
Colin Thurston
Digital interface with icons for policies, regulations and law highlighting data compliance concepts.
Credit: iStock

Keeping pace with evolving data compliance requirements is essential to maintaining research integrity, avoiding costly errors, and unlocking the full value of your data. Yet for many labs, the complexity of managing disparate systems, inconsistent data formats, and growing regulatory scrutiny can feel overwhelming.


This article explores how forward-thinking organizations are addressing these challenges. From ensuring data accuracy at the point of capture to making legacy datasets AI-ready, discover practical strategies that can strengthen your compliance framework without slowing innovation. Continue reading to gain insight into how emerging technologies are reshaping the way labs manage, analyze, and report data.

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Meet the Author
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RJ Mackenzie
Freelance Science Writer & Journalist
RJ is a freelance science writer based in Glasgow. He covers biological and biomedical science, with a focus on the complexities and curiosities of the brain and emerging AI technologies. RJ was a science writer at Technology Networks for six years, where he also worked on the site’s SEO and editorial AI strategies. He created the site’s podcast, Opinionated Science, in 2020. RJ has a Master’s degree in Clinical Neurosciences from the University of Cambridge.
Interviewing
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Colin Thurston
Business Development Manager
Colin Thurston is a business development manager at informatics consultancy Scimcon. He has 25 years of experience in the scientific data and laboratory informatics field. He is also a freelance consultant, advising on deployment and management of LIMS, CDS and ELN.
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